• 学术搜索
  • 科研智能体
    • Research Labs
    • AI 阅读
    • AI 文库
    • 深度研究
    • 学者亮点
  • 学术资源
    • AI2000
    • 期刊/会议
    • 学者库
    • 学术API
    • 溯源树
    • 数据集
  • 知识沉淀
    • 学术空间
订阅小程序
旧版功能
aminer vip
开通会员低至0.73元/天
一次搞定AI科研
立即登录
  • English
  • 联系方式
    S

    Save Ourselves Breast Cancer Organization

    EST. 1991
    10论文总数
    104引用总数

    论文量&引用量时间轴

    机构学者

    排序
    James Brodman
    James Brodman
    Intel Corporation
    论文:2引用:0H-index:0
    James Reinders
    James Reinders
    Intel Corporation
    论文:2引用:0H-index:0
    Xinmin Tian
    Xinmin Tian
    论文:2引用:0H-index:0
    Ben Ashbaugh
    Ben Ashbaugh
    Intel Corporation
    论文:2引用:0H-index:0
    S. J. Pennycook
    S. J. Pennycook
    Intel Corporation
    论文:2引用:0H-index:0
    Michael Kinsner
    Michael Kinsner
    Intel Corporation
    论文:2引用:0H-index:0
    Steven E.R. Hovius
    Steven E.R. Hovius
    Radboud University Medical Centre (Radboudumc)
    论文:1引用:0H-index:0
    James E Baumgardner
    James E Baumgardner
    Oscillogy LLC
    论文:1引用:0H-index:0
    Patrick Lorea
    Patrick Lorea
    Laboratoire de chirurgie plastique expérimentale, CHU Brugmann
    论文:1引用:0H-index:0

    论文(10)

    年份
    起
    –
    止
    排序
    1Secure Authorization and Traffic Congestion Prediction in VANET Using R3-DWT and EDICNN with Blockchain
    Swapna Narla, Sai Sathish Kethu, Qaisar Abbas, Sreekar Peddi, Dharma Teja Valivarthi, N. Purandhar

    A Secure Transportation System (STS) improves traffic safety and enables vehicles to pass through non-congested routes. However, none of the prevailing works concentrated on protecting the data used for authorization in STS. Therefore, the secure authorization and Traffic Congestion Prediction (TCP) model is proposed. Initially, the user registers into blockchain and a key is generated using Koblitz Torus Curve Cryptography (KTCC). Then, the network is initialized and vehicle information is sensed, and then using KTCC, the data are secured. From the sensed data, the hash code is generated using Entropy Davies-Meyer Streebog (EDM-Streebog). Meanwhile, the vehicle's number-plates are detected using You Only Look Once-Version 8 (YOLOV8). Now, in the number-plate image, the watermarking is done to protect the hash code through R-squared Regression Discrete Wavelet Transform (R3-DWT). Next, the hash code is retrieved in the blockchain and the verification is processed. For the verified hash, the secured data are decrypted and TCP is done. To train the TCP model, the high traffic video data are collected and pre-processed. Then, the day/night frame is identified. Then, the image conversion of the night frame is done and along with the day frame, the vehicle detection in the frame is done by YOLOV8. From the vehicle detected image, the vehicle tracking is done and then using Elliott Deep Identity Convolutional Neural Network (EDICNN), the TCP is made. Thus, the congestion details are notified to users for secure transportation. The proposed work thus predicted the traffic congestion effectively with an accuracy of 98.0213%, and recall of 98.3024%.

    2026INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE AND APPLICATIONS(2026)
    引用
    AI阅读
    加入学术空间
    2Backend Interoperability
    James Reinders,Ben Ashbaugh,James Brodman,Michael Kinsner,John Pennycook,Xinmin Tian

    AbstractChapter 20 describes backend interoperability, a SYCL feature that can be used to incrementally add SYCL to an application that is already using other data-parallel techniques or APIs, or to use other data-parallel APIs directly from our SYCL applications.

    2023Data Parallel C++(2023)
    引用
    AI阅读
    加入学术空间
    3Defining Kernels
    James Reinders,Ben Ashbaugh,James Brodman,Michael Kinsner,John Pennycook,Xinmin Tian

    Thus far in this book, our code examples have represented kernels using C++ lambda expressions. Lambda expressions are a concise and convenient way to represent a kernel right where it is used, but they are not the only way to represent a kernel in SYCL. In this chapter, we will explore various ways to define kernels in detail, helping us to choose a kernel form that is most natural for our C++ coding needs.

    2023Data Parallel C++(2023)
    引用
    AI阅读
    加入学术空间
    4The War in the North Sea: the Royal Navy and the Imperial German Navy 1914–1918
    Harold N. Boyer

    "The War in the North Sea: The Royal Navy and the Imperial German Navy 1914–1918." The Mariner's Mirror, 104(2), pp. 241–242

    2018MARINERS MIRROR(2018)
    引用
    AI阅读
    加入学术空间
    5Specifics of Wound Closure
    Brittany Busse
    2016Wound Management in Urgent Care(2016)
    引用
    AI阅读
    加入学术空间
    立即登录,查看全部 10 篇论文

    合作机构(13)

    ZRT Laboratory合作论文 2
    Xcel Energy (United States)合作论文 1
    Pinnacle Clinical Research合作论文 1
    Michigan Science Center合作论文 1
    Imam Muhammad ibn Saud Islamic University合作论文 1
    Energy & Meteo Systems (Germany)合作论文 1
    国家海洋和大气管理局合作论文 1
    国家可再生能源实验室合作论文 1
    Plano Cancer Institute合作论文 1
    伦斯勒理工学院合作论文 1

    机构统计